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Record W2804362929 · doi:10.3389/fpls.2018.00775

Using RT-qPCR, Proteomics, and Microscopy to Unravel the Spatio-Temporal Expression and Subcellular Localization of Hordoindolines Across Development in Barley Endosperm

2018· article· en· W2804362929 on OpenAlexfundno aff
Azita Shabrangy, Valentin Roustan, Siegfried Reipert, Marieluise Weidinger, Pierre-Jean Roustan, Eva Stöger, Wolfram Weckwerth, Verena Ibl

Bibliographic record

VenueFrontiers in Plant Science · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsnot available
FundersUniversität für Bodenkultur WienAustrian Science FundUniversity of Ottawa
KeywordsEndospermBiologySubcellular localizationProteomicsCell biologyBotanyComputational biologyGeneticsGeneCytoplasm

Abstract

fetched live from OpenAlex

Hordeum vulgare (barley) hordoindolines (HINs), HINa, HINb1 and HINb2, are orthologous proteins of wheat puroindolines (PINs) that are small, basic, cysteine-rich seed-specific proteins and responsible for grain hardness. Grain hardness, is, next to its protein content, a major quality trait. In barley, HINb is most highly expressed in the mid-stage developed endosperm and is associated with both major endosperm texture and grain hardness. However, data required to understand the spatio-temporal dynamics of HIN transcripts and HIN protein regulation during grain filling processes are missing. Using reverse transcription quantitative PCR (RT-qPCR) and proteomics we analyzed HIN transcript and HIN protein abundance from whole seeds (WSs) at four ((6 days after pollination (dap), 10 dap, 12 dap and ≥ 20 dap)) as well as from aleurone, subaleurone and starchy endosperm at two (12 dap and ≥ 20 dap) developmental stages. At the WS level, results from RT-qPCR, proteomics and western blot showed a continuous increase of HIN transcript and HIN protein abundance across these four developmental stages. Miroscopic studies revealed HIN localization mainly at the vacuolar membrane in the aleurone, at protein bodies (PBs) in subaleurone and at the periphery of starch granules in the starchy endosperm. Laser microdissetion (LMD) proteomic analyses identified HINb2 as the most prominent HIN protein in starchy endosperm at ≥ 20 dap. Additionally, our quantification data revealed a poor correlation between transcript and protein levels of HINs in subaleurone during development. Here, we correlated data achieved by RT-qPCR, proteomics and microscopy that reveal different expression and localization pattern of HINs in each layer during barley endosperm development. This indicats a contribution of each tissue to the regulation of HINs during grain filling. The effect of the high protein abundance of HINs in the starchy endosperm and their localization at the periphery of starch granules at late development stages at the cereal-based end-product quality is discussed. Understanding the spatio-temporal regulated HINs is essential to improve barley quality traits for high end-product quality, as hard texture of the barley grain is regulated by the ratio between HINb/HINa.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.269
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2018
Admission routes1
Has abstractyes

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